Fuzzy and Neural Adaptive Control of a Class of Nonlinear Systems Год выпуска: 2012Автор: Mohamed Bahita and Khaled BelarbiИздательство: LAP Lambert Academic PublishingСтраниц: 64ISBN: 9783848489206Описание In this book, two types of direct adaptive control schemes for a class of nonlinear systems are proposed. Based on the feedback linearization theory, the architecture employs for the first approach the fuzzy logic reasoning of Takagi Sugeno (TS) type and uses for the second approach the strategy of neural network reasoning of radial basis function (RBF) type to approximate the feedback linearization control law. In each case, the parameters of the adaptive controller are adapted according to a law derived using Lyapunov stability theory. The adaptive controller is applied in simulation to control three nonlinear systems in both the fuzzy and the neural network methods.
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Ирина Юлия, добрый вечер! Я сдала диплом после вашего сопровождения на 5. Спасибо Вам! Конечно все выводы и заключения наши были исправленны! Однако, хочу сказать, что мы двоем защищались у этого научного руководителя и все было достойно! Я не верила, что в МГУ серьезные требования!!! Ан нет!!! Всего Вам доброго! Все-равно спасибо!!!
